Although collaborative 3D perception has successfully improved detection performance by
sharing LIDAR information among multiple agents, its impact under adverse weather is …

Object detection is becoming increasingly critical in autonomous driving. However, the
accuracy and effectiveness of object detectors are often constrained by the obscuration of …

Adverse weather conditions can severely affect the performance of LiDAR sensors by
introducing unwanted noise in the measurements. Therefore, differentiating between noise …

Autonomous vehicles rely on camera, LiDAR, and radar sensors to navigate the
environment. Adverse weather conditions like snow, rain, and fog are known to be …

Although lidar sensors have emerged as a cornerstone sensing modality in autonomous
driving, they face significant challenges in adverse weather conditions. A particularly …

This study addresses the limitations of existing autonomous vehicle datasets, particularly the
need for greater specificity of weather conditions and road types. We utilized X-CAR to …

The current three‐dimensional target detection algorithm for smart cars mainly uses three‐
dimensional point cloud data collected by LiDAR. Effectively detect target objects in three …